Remote sensing utility expansion through Earth Portal internet browser

A modular, graphic-oriented Internet browser has been developed to enable non-technical client access to a literal spinning world of information and remotely sensed. The Earth Portal (www.earthportal.net) uses the ManyOne browser (www.manyone.net) to provide engaging point and click views of the Earth fully tessellated with remotely sensed imagery and geospatial data. The ManyOne browser technology use Mozilla with embedded plugins to apply multiple 3-D graphics engines, e.g. ArcGlobe or GeoFusion, that directly link with the open-systems architecture of the geo-spatial infrastructure. This innovation allows for rendering of satellite imagery directly over the Earth's surface and requires no technical training by the web user. Effective use of this global distribution system for the remote sensing community requires a minimal compliance with protocols and standards that have been promoted by NSDI and other open-systems standards organizations.

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.

Multi-utility finance : a problematic case

This paper treats one particular version of the multi-utility strategy as experienced by the Hyder Group. We examine some aspectw of the company's financial performance and consider the implications.

Spreadsheet Conditional Formatting Illuminates Investigations into Modular Arithmetic

Modular arithmetic has often been regarded as something of a mathematical curiosity, at least by those unfamiliar with its importance to both abstract algebra and number theory, and with its numerous applications. However, with the ubiquity of fast digital computers, and the need for reliable digital security systems such as RSA, this important branch of mathematics is now considered essential knowledge for many professionals. Indeed, computer arithmetic itself is, ipso facto, modular. This chapter describes how the modern graphical spreadsheet may be used to clearly illustrate the basics of modular arithmetic, and to solve certain classes of problems. Students may then gain structural insight and the foundations laid for applications to such areas as hashing, random number generation, and public-key cryptography.

Approximate solutions to stochastic dynamic programs

This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified. © 1997 Cambridge University Press.

ERP stakeholders’ perceptions of data quality and utility

While data quality has been identified as a critical factor associated with enterprise resource planning (ERP) failure, the relationship between ERP stakeholders, the information they require and its relationship to ERP outcomes continues to be poorly understood. Applying stakeholder theory to the problem of ERP performance, we put forward a framework articulating the fundamental differences in the way users differentiate between ERP data quality and utility. We argue that the failure of ERPs to produce significant organisational outcomes can be attributed to conflict between stakeholder groups over whether the data contained within an ERP is of adequate ‘quality’. The framework provides guidance as how to manage data flows between stakeholders, offering insight into each of their specific data requirements. The framework provides support for the idea that stakeholder affiliation dictates the assumptions and core values held by individuals, driving their data needs and their perceptions of data quality and utility.

Clinical utility of exhaled nitric oxide

Lower airway inflammation is generally classified as eosinophilic or neutrophilic. In conditions where eosinophilic inflammation predominates such as asthma in children, corticosteroids are usually beneficial. Traditionally, lower airway eosinophilia is measured using cellular count (through bronchoalveolar lavage or induced sputum). Both methods have limited applicability in children. When instruments to measure fractional exhaled nitric oxide (FeNO) became available, it presented an attractive option as it provided a non-invasive method of measuring eosinophilic inflammation suitable for children and adult. Not surprisingly, proposals have been made that FeNO measurement can be clinically used in many scenarios including monitoring the response to anti-inflammatory medications, to verify the adherence to treatment, and to predict upcoming asthma exacerbations. This thesis addresses the utility of FeNO levels in various scenarios, specifically in relation to asthma control and cough, a contentious aspect of the diagnosis of asthma. The thesis consists of a series of systematic reviews (related to the main question) and original studies in children. The over-arching aim of the thesis is to determine if FeNO is a clinically useful tool in the management of asthma and common asthma symptoms. The specific aims of the thesis were, to: 1. Determine if children with asthma have more severe acute respiratory symptoms at presentation with an asthma exacerbation and at days 7, 10 and 14 using validated scales. We also examined if children with asthma were more likely to have a persistent cough on day 14 than children with protracted bronchitis and/or controls. 2. Evaluate the efficacy of tailoring asthma interventions based on sputum analysis in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. 3. Evaluate the efficacy of tailoring asthma interventions based on exhaled nitric oxide in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. 4. Determine if adjustment of asthma medications based on FeNO levels (compared to management based on clinical symptoms) reduces severe exacerbations in children with asthma. 5. Examine the relationship between FeNO and exercise induced broncho-constriction and cough in children The aims above are addressed in respective chapters and all but one has been published/submitted. A synopsis of the findings are: In study-1 (Aim 1), we found that children with protracted bronchitis had the most severe acute respiratory infection symptoms and higher percentage of respiratory morbidity at day 14 in comparison to children with asthma and healthy controls. The systematic review of study-2 (Aim 2) included 246 randomised adult participants (no children) with 221 completing the trials. In the meta-analysis, a significant reduction in number of participants who had one or more asthma exacerbations occurred when treatment was based on sputum eosinophils in comparison to clinical symptoms. In the systematic review of study-3 (Aim 3), we found no significant difference between the intervention group (treatment adjusted based on FeNO) and control group (treatment adjusted based on clinical symptoms) for the primary outcome of asthma exacerbations or for the other outcomes (clinical symptoms, FeNO level and spirometry). In post-hoc analysis, a significant reduction in mean final daily dose ICS per adult was found in the group where treatment was based on FeNO in comparison to clinical symptoms. In contrast, in the paediatric studies, there was a significant increase in ICS dose in the FeNO strategy arm. Thus, controversy remains of the benefit or otherwise of utilising exhaled nitric oxide (FeNO) in routine clinical practice. FeNO levels are dependent on atopy and none of the 7 published trials have considered atopic status in FeNO levels when medications were adjusted. In study-4 (Aim 4), 64 children with asthma were recruited. Their asthma medications were adjusted according to either FeNO levels or usual clinical care utilising a management hierarchy taking into account atopy. It was concluded that tailoring of asthma medications in accordance to FeNO levels (compared to usual management), taking into account atopy status, reduced the number of children with severe exacerbations. However, a FeNO-based strategy resulted in higher daily ICS doses and had no benefit on asthma control. In study-5 (Aim 5), 33 children with cough and 17 controls were recruited. They were randomised to undertake an exercise challenge on day 1, or dry powder mannitol challenge on day 1 (with alternative challenge being done on day 2). In addition, a 24 hour cough meter, skin prick test, capsaicin cough sensitivity test and cough diary were undertaken. The change in cough frequency post exercise was significantly increased in the children with cough. FeNO decreases post exercise regardless of whether EIB is present or not. Limitations in the studies were addressed in the respective chapters. In summary, the studies from this thesis have provided new information on: • The severity of respiratory symptoms was increased in the early phase of the asthma exacerbation but not in the later recovery phase when compared with controls. • The utility of FeNO in the management of children with asthma. • The relationship of FeNO, cough and EIB in children. • Systematic reviews on the efficacy of tailoring asthma interventions based on eosinophilic inflammatory markers (sputum analysis and FeNO) in comparison to clinical symptoms.

Demand Response for Residential Appliances in a Smart Electricity Distribution Network: Utility and Customer Perspectives

This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

Developing affordable and sustainable housing through energy, transport, and building utility integration

Housing affordability and sustainable development are not polarised ideologies as both are necessary with increasing urbanisation. We must bridge the gap between current median house pricing and target affordable house pricing whilst pursuing sustainability. This paper examines the potential of initial construction cost and ongoing utilities and transport cost reduction through the integration of sustainable housing design and transit oriented development principles in a Commuter Energy and Building Utilities System (CEBUS). It also introduces current research on the development of a Dynamic Simulation Model for CEBUS applications in the Australian property development and construction industry.

Modeling conditional correlations of asset returns : a smooth transition approach

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

Clinical outcomes, not clinical utility, should be the major consideration for saxagliptin with or without metformin

A recent review by Panagoulias and Doupis, published in Patient Preference and Adherence, concerned the saxagliptin/metformin fixed combination (SAXA/MET FDC), and was titled "Clinical utility in the treatment of type 2 diabetes with the saxagliptin/metformin fixed combination."1 This review concluded that "The SAXA/MET FDC is a patient-friendly, dosage-flexible, and hypoglycemia-safe regimen with very few adverse events and a neutral or even favorable effect on body weight. It achieves significant glycosylated hemoglobin A1c reduction helping the patient to achieve his/her individual glycemic goals."1

Deriving a preference-based utility measure for cancer patients from the European Organisation for the Research and Treatment of Cancer's Quality of Life Questionnaire C30 : a confirmatory versus exploratory approach

Background Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. Aim To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer’s core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. Methods QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. Results CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker–Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. Conclusion CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.